Stochastic models

The Devices and Services Security team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to secure the development of industry-leading Generative AI systems. As a Senior Applied Scientist with the Devices & Services Security team, you will lead the development of novel algorithms and modeling techniques to advance the state of the art with Generative AI systems. Your work will directly impact our customers in the form of products and services that make use of vision and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development of security solutions with multimodal Large Language Models (LLMs) and Generative Artificial Intelligence (Gen AI). The Devices and Services (D&S) Security team works to ensure that Amazon devices and services are designed and implemented to the high standards required to maintain and enhance customer trust. The team develops security technologies for builder teams, performs penetration testing, and handles and tracks incident responses to resolution. The team is responsible for defining and executing on the security and privacy requirements for the entire organization. A day in the life Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

We are seeking an Applied Scientist to join our AI Security team, which builds security tooling and paved path solutions to ensure Generative AI (GenAI) based experiences developed by Amazon uphold our high security standards, and uses AI to develop foundational services that make security mechanisms more effective and efficient. As an Applied Scientist, you’ll be responsible for designing and implementing state-of-the-art solutions, to build an AI-based foundational service for securing products and services at Amazon scale. You will collaborate with applied scientists and software engineers to develop innovative technologies to solve some of our hardest security problems, and AI-based security solutions that support builder teams across Amazon throughout their software development journey, enabling Amazon businesses to strengthen their security posture more efficiently and effectively. Key job responsibilities • design and implement accurate and scalable methods to solve our hardest AI security problems • Lead and partner with applied scientists and software development engineers to drive technical design and implementation for a foundational GenAI-based security service About the team The mission of the AI Security organization is to ensure Generative AI experiences delivered by Amazon to our customers uphold our high security standards and to harness AI to strengthen Amazon’s security posture more efficiently and effectively. A day in the life A day in the life involves meeting Vulnerability Management and Incident Responder teams to review data flows, prediction use cases, and automation gaps. From here you will research data sets, working with security/software engineers to retrieve data needed for your analysis and explorations. Once you have framed the problems, you will conduct experiments, regressions, and various analysis activities to find insights. You will develop and train models that will then be placed into a production environment with the help of software engineers. You will then work with your security team partners to understand the effectiveness of the models created. About the team The Defensive Security team is small, tight-knit, and located in Austin, Texas. It is primarily software engineers, but will be developed into a hybrid team of software engineers and security engineers. This team will have tenured Amazonian leadership, with a track record of mentoring, coaching, and career progression support. About Amazon Security Diverse Experiences — Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? — At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture — In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth — We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance — We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Amazon’s maps play a crucial role in our vehicle navigation, routing, and planning problems to ensure fast and safe deliveries to our customers. As part of the Last Mile Geospatial Science organization, you’ll partner closely with other scientists and engineers in a collegial environment with a clear path to business impact. We have an exciting problem area to augment the maps and routing inputs from satellite/aerial imagery and street videos by leveraging the latest computer vision and deep learning techniques. Key job responsibilities Successful candidates should have a deep knowledge (both theoretical and practical) of various machine learning algorithms for large scale computer vision problems, the ability to map models into production-worthy code, the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers, and the excitement to take iterative approaches to tackle big, long term problems. The applied scientist should be proficient with image and video analysis using machine learning, including designing architecture from scratch, modify existing loss functions, full model training, fine-tuning, and evaluating the latest deep learning models. The Applied Scientist optimizes different models for specific platforms, including edge devices with restricted resources. Multi-modal models, e.g., Large Vision Language Models (LVLM), zero-shot, few-shot, and semi-supervised learning paradigms are used extensively. A day in the life If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan

We are seeking a talented and analytical Data Scientist to join our team and drive data-driven insights and solutions. In this role, you will be responsible for performing exploratory data analysis, developing and deploying predictive models, and leveraging advanced analytics techniques to uncover valuable insights and support data-driven decision-making across the organization. Key job responsibilities • Collaborate with our applied and data scientists to build robust and scalable Generative AI solutions for business problems • Effectively use Foundation Models available on Amazon Bedrock and Amazon SageMaker to meet our customer's performance needs • Work hands on to build scalable cloud environment for our customers to label data, build, train, tune and deploy their models • Interact with customer directly to understand the business problem, help and aid them in implementation of their ML ecosystem • Analyze and extract relevant information from large amounts of historical data to help automate and optimize key processes • Work closely with partner teams to drive model implementations and new algorithms About the team Amazon Web Services (AWS) provides a scalable cloud computing platform to companies globally. AWS Global Services (GS), formed in 2022, delivers customer success throughout the cloud adoption lifecycle. Our 25K+ employees and integrated offerings enable us to combine technology and human expertise to maximize and accelerate customer outcomes. GS is comprised of four primary business units: 1) Global Services Security (GSS) provides security guidance and offerings, 2) Training & Certification (T&C) offers cloud skills training and certification, 3) Professional Services (ProServe) provides consulting and hands-on-keyboard services, and 4) Support and AWS Managed Services (Support) delivers 24/7 technical support and managed services. Together, these teams continuously improve our systems and processes to enable better results for both customers and employees, with the GS Strategy & Operations (GSS) teams supporting each. GSSO enables integrated business support, product management, planning, and deal strategy for GS. GSSO understands customer experiences and inspires bold ideas to deliver the best experiences and solutions to our customers. We embrace scientific thinking, pursue continuous improvement, and develop talent to provide world-class support across GS. About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our US Amazon offices.

We are looking for talented Applied Scientists who are adept at a variety of skills, especially with LLMs, use of edge devices, computer vision, or related foundational models that will accelerate our plans to generate high-quality defect detection mechanisms. Our mission is to improve the reliability of equipment (conveyors, motors, belts), and effectively identify from sensors, images, and video specific actions on material handling equipment (MHE) that can prevent unplanned downtime. With millions of products available on Amazon.com comes variation in weight, size, material, and shape. We build products and systems to detect and prevent equipment downtime using a diverse set of classification and anomaly detection algorithms including LLMs. We screen over 150 million events every day, and process this data to create real time alerting systems. We are still day 1 and have an exciting roadmap to build AI predictive maintenance models, deploy scalable causal inference solutions to measure the impact of events, and optimize the reliability of conveyance helping Amazon scale for years to come. As an Applied Scientist II, you will design, develop, and maintain scalable, Artificial Intelligence models with automated training, validation, monitoring and reporting. You will work closely with other scientists and engineers to architect and develop new learning algorithms and prediction techniques. You will collaborate with product managers and engineering teams to design and implement scientific solutions for Amazon problems. Provide technical and scientific guidance to your team members. Contribute to the research community, by working with other scientists across Amazon and publish papers at peer reviewed journals and conferences. Key job responsibilities - Design and implement scalable infrastructure that enables stacked deep learning models to detect a variety of defects in fractions of a second; - Design and implement anomaly detection and large language models to identify defects associated with customer packages; - Experiment and scale models to thousands of sites worldwide; - Collaborate with RME internal and external stakeholders and have a cross-team impact; - Create and share with audiences of varying levels technical papers and presentation. About the team We are a growing team of applied, research, and data scientists working together with an engineering team and product managers to create the next-generation IIoT platform for the Reliability and Maintenance Engineering org.

Amazon continues to invest heavily in building our world class advertising business. Our products are strategically important to our Retail and Marketplace businesses, driving long term growth. We deliver billions of ad impressions and millions of clicks daily, breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and strong bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.The Sponsored Products OSSR team is responsible for all non-search supply and associated experiences. As an Applied Scientist on our team, you will be responsible for defining the science and technical strategy for one of our most impactful strategic initiatives, creating lasting value for Amazon and our advertising customers. Key job responsibilities • Support business, science and engineering strategy and roadmap for Sponsored Products OSSR projects • Drive alignment across organizations for science, engineering and product strategy to achieve business goals • Lead/guide scientists and engineers across teams to develop, test, launch and improve of science models designed to optimize the shopper experience and deliver long term value for Amazon and advertisers • Develop state of the art experimental approaches and ML models. About the team Sponsored Products (SP) is Amazon's largest and fastest growing business. Over the last few years we grown to a multi-billion dollar business. SP ads are shown prominently throughout search and detail pages, allowing shoppers to seamlessly discover products sold on Amazon. Ad experience and market place is one of the highest impact decisions we make. This role has unparalleled opportunity to grow our marketplace and deliver value for advertisers and shoppers.

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist II in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.

An information-rich and accurate product catalog is a strategic asset for Amazon. It powers unrivaled product discovery, informs customer buying decisions, offers a large selection, and positions Amazon as the first stop for shopping online. We use data analysis and statistical and machine learning techniques to proactively identify relationships between products within the Amazon product catalog. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages) and multitude of input sources (millions of sellers contributing product data with different quality). Amazon’s Item and Relationship Identity Systems group is looking for an innovative and customer-focused applied scientist to help us make the world’s best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services to infer product-to-product relationships that matter to our customers. You will work in a collaborative environment where you can experiment with massive data from the world’s largest product catalog, work on challenging problems, quickly implement and deploy your algorithmic ideas at scale, understand whether they succeed via statistically relevant experiments across millions of customers. Key job responsibilities * Map business requirements and customer needs to a scientific problem. * Align the research direction to business requirements and make the right judgments on research/development schedule and prioritization. * Research, design and implement scalable machine learning (ML) techniques to solve problems that matter to our customers in an iterative fashion. * Design, experiment and evaluate highly innovative models for predictive, explainable learning * Partner with other scientists to build state-of-the-art ML systems powering Amazon * Work closely with software engineering teams to drive real-time model experiments, implementations and new feature creations * Stay informed on the latest machine learning, natural language and/or artificial intelligence trends and make presentations to the larger engineering and applied science communities. About the team The IRIS team owns programs and systems to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog. We focus on the following areas: 1) reducing customer perceived duplicates: eliminating all duplicate ASINs that are indistinguishable by customers and identifying broken and missing variations, 2) reducing product detail page inconsistency: preventing inconsistent item identities, and improving the customer experience by automatically detecting and creating factual relationships between ASINs: e.g. variation families, newer versions, 3) reducing selling partner listing friction: reducing GTIN defects in the catalog, and false conflicts in contributions, and 4) improving brand customer experience: providing a strong brand identity to contributions and ASINs, by matching them to Universal Brand Catalog brand entities.

Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences